import pandas as pd
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import MinMaxScaler

dataFilePath = r'C:\Users\yun\Desktop\Bike-Sharing-Dataset\day.csv'
df = pd.read_csv(dataFilePath)
categorical_feature=['season','mnth','weathersit','weekday']
for col in categorical_feature:
    df[col]=df[col].astype('object')
    
x_train_cat=df[categorical_feature]
x_train_cat=pd.get_dummies(x_train_cat)
x_train_cat.head()